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Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

Medicine and Health

Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

S. A. Harmon, T. H. Sanford, et al.

This groundbreaking study reveals that deep learning algorithms, trained with data from 1280 international patients, can detect COVID-19 pneumonia in chest CT scans with impressive accuracy—up to 90.8%. This research, conducted by a dedicated team of authors, underscores the exciting potential of AI in rapid and precise medical evaluations.

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Playback language: English
Abstract
This study demonstrates that deep learning algorithms, trained on a diverse international cohort of 1280 patients, can accurately detect COVID-19 pneumonia on chest CT scans. The algorithms achieved up to 90.8% accuracy, 84% sensitivity, and 93% specificity in an independent test set of 1337 patients. The study highlights the potential of AI to aid in rapid and accurate evaluation of CT scans for COVID-19.
Publisher
Nature Communications
Published On
Nov 16, 2020
Authors
Stephanie A Harmon, Thomas H Sanford, Sheng Xu, Evrim B Turkbey, Holger Roth, Ziyue Xu, Dong Yang, Andriy Myronenko, Victoria Anderson, Amel Amalu, Maxime Blain, Michael Kassin, Dilara Long, Nicole Varble, Stephanie M Walker, Ulas Baci, Anna Maria Ierardi, Elvira Stellato, Guido Giovanni Plensich, Giuseppe Franceschelli, Cristiano Girelloni, Giovanni Irmici, Dominic Labella, Dima Hammoud, Ashkan Malayeri, Elizabeth Jones, Ronald M Summers, Peter L Choyke, Daguang Xu, Mona Flores, Kaku Tamura, Hioriumi Obinata, Hitoshi Mori, Francesca Patella, Maurizio Caritati, Gianpaolo Carraieillo, Peng An, Bradford J Wood, Baris Turkbey
Tags
deep learning
COVID-19
CT scans
pneumonia detection
artificial intelligence
medical imaging
accuracy

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